QA Lead
Posted Updated
Person with good understanding of standard enterprise software development lifecycle
(SDLC)
• Ability to work without specs in the first few months
• Initiative and good, pro-active synchronous communication
• Good automation background (playwright/selenium/cypress)
• Some experience defining test strategies
• Hands-on experience using modern AI tools (LLMs/agents) to accelerate QA activities
(e.g., test design, test scripts generation, requirements analysis)
—————————————————————————
QA Lead
As the QA Lead, you will define and execute the quality strategy for an agentic AI engine that
automates the software development lifecycle. You will ensure the reliability, correctness, and
safety of the platform and its core capabilities, and support validation of multi-agent workflows
where needed.
Responsibilities
• Establish the overall QA strategy, quality standards, and quality gates for the platform
and enterprise-grade systems.
• Build and maintain automated testing and evaluation pipelines covering functional, non-
functional, safety, and performance testing for the platform (including REST APIs,
integrations, and core runtime components).
• Develop and maintain automated test suites and regression systems for platform
capabilities and REST APIs.
• Validate reliability, correctness, and backward compatibility of platform releases,
including risk-based testing and coverage of critical user paths.
• Partner with architects, engineers, and product teams to define testability requirements,
acceptance criteria, and failure modes, proactively contributing to requirement
clarification and formalization in the absence of complete specs.
• Monitor quality metrics and provide insights, risks, and improvement recommendations.
• Support rapid iteration cycles, ensuring consistent platform stability and predictable
behavior across environments.
• Optionally, conduct validation of outputs generated by agent squads/workflows across
the SDLC (specs, designs, code, tests) when required, focusing on accuracy, consistency,
and safety.
Technical Requirements
• Experience planning, validating, and testing systems where business specifications
cannot be fully predefined (e.g. rule engine systems, decision automation, early-stage
products with evolving requirements).
• Strong skills for building automated tests, test harnesses, and evaluation scripts.
• Experience testing REST APIs and integrating QA automation with CI/CD.• Hands-on experience applying LLMs/agentic tools in QA processes (e.g., generating test
cases and test scripts, accelerating exploratory testing, requirements analysis, defining
acceptance criteria, creating test data).
• Understanding of AI safety and security testing, including prompt-injection tests and red
teaming is a plus.
Soft Skills Requirements
• Strong ownership, adaptability, and ability to work in fast-paced, iterative environments.
• Proactive mindset and ability to drive clarity when requirements and documentation are
incomplete.
• Effective communication and cross-functional collaboration.
• Interest in early-stage product development and AI-driven software engineering.
• English: Upper-Intermediate/Advanced.
(SDLC)
• Ability to work without specs in the first few months
• Initiative and good, pro-active synchronous communication
• Good automation background (playwright/selenium/cypress)
• Some experience defining test strategies
• Hands-on experience using modern AI tools (LLMs/agents) to accelerate QA activities
(e.g., test design, test scripts generation, requirements analysis)
—————————————————————————
QA Lead
As the QA Lead, you will define and execute the quality strategy for an agentic AI engine that
automates the software development lifecycle. You will ensure the reliability, correctness, and
safety of the platform and its core capabilities, and support validation of multi-agent workflows
where needed.
Responsibilities
• Establish the overall QA strategy, quality standards, and quality gates for the platform
and enterprise-grade systems.
• Build and maintain automated testing and evaluation pipelines covering functional, non-
functional, safety, and performance testing for the platform (including REST APIs,
integrations, and core runtime components).
• Develop and maintain automated test suites and regression systems for platform
capabilities and REST APIs.
• Validate reliability, correctness, and backward compatibility of platform releases,
including risk-based testing and coverage of critical user paths.
• Partner with architects, engineers, and product teams to define testability requirements,
acceptance criteria, and failure modes, proactively contributing to requirement
clarification and formalization in the absence of complete specs.
• Monitor quality metrics and provide insights, risks, and improvement recommendations.
• Support rapid iteration cycles, ensuring consistent platform stability and predictable
behavior across environments.
• Optionally, conduct validation of outputs generated by agent squads/workflows across
the SDLC (specs, designs, code, tests) when required, focusing on accuracy, consistency,
and safety.
Technical Requirements
• Experience planning, validating, and testing systems where business specifications
cannot be fully predefined (e.g. rule engine systems, decision automation, early-stage
products with evolving requirements).
• Strong skills for building automated tests, test harnesses, and evaluation scripts.
• Experience testing REST APIs and integrating QA automation with CI/CD.• Hands-on experience applying LLMs/agentic tools in QA processes (e.g., generating test
cases and test scripts, accelerating exploratory testing, requirements analysis, defining
acceptance criteria, creating test data).
• Understanding of AI safety and security testing, including prompt-injection tests and red
teaming is a plus.
Soft Skills Requirements
• Strong ownership, adaptability, and ability to work in fast-paced, iterative environments.
• Proactive mindset and ability to drive clarity when requirements and documentation are
incomplete.
• Effective communication and cross-functional collaboration.
• Interest in early-stage product development and AI-driven software engineering.
• English: Upper-Intermediate/Advanced.